In this paper, we propose a novel method DeepSCC for source code classification, which is based on fine-tuned RoBERTa [1]}. To show the effectiveness of DeepSCC, we used four widely used performance measures to evaluate the performance of DeepSCC. The results show the competitiveness of DeepSCC when compared to nine state-of-the-art baselines from the fields of source code classification and neural text classification.
